activity
20162021
most citedDeployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

49 citations · 81 across the 12 of their papers we have counts for

collaborators

28 papers

cs.CL2021

AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages

Machel Reid, Junjie Hu, Graham Neubig +1

Reproducible benchmarks are crucial in driving progress of machine translation research. However, existing machine translation benchmarks have been mostly limited to high-resource…

cs.AI2021

Estimating Disentangled Belief about Hidden State and Hidden Task for Meta-RL

Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo

There is considerable interest in designing meta-reinforcement learning (meta-RL) algorithms, which enable autonomous agents to adapt new tasks from small amount of experience. In…

cs.LG2021

Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning

Hiroki Furuta, Tadashi Kozuno, Tatsuya Matsushima +2

Recently many algorithms were devised for reinforcement learning (RL) with function approximation. While they have clear algorithmic distinctions, they also have many implementatio…

cs.LG2021

Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning

Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno +4

Progress in deep reinforcement learning (RL) research is largely enabled by benchmark task environments. However, analyzing the nature of those environments is often overlooked. In…

cs.LG20212 cited

Group Equivariant Conditional Neural Processes

Makoto Kawano, Wataru Kumagai, Akiyoshi Sannai +2

We present the group equivariant conditional neural process (EquivCNP), a meta-learning method with permutation invariance in a data set as in conventional conditional neural proce…

cs.LG2021

Wheelchair Behavior Recognition for Visualizing Sidewalk Accessibility by Deep Neural Networks

Takumi Watanabe, Hiroki Takahashi, Goh Sato +3

This paper introduces our methodology to estimate sidewalk accessibilities from wheelchair behavior via a triaxial accelerometer in a smartphone installed under a wheelchair seat.…